China's energy-intensive industries utilize the leading proportion of coal to meet the demand for its industrial outputs, while on the other hand, these industries also assure the provision of livelihood to millions of people, and capping the share of coal consumption for these industries can adversely affect the industrial and economic growth of China. Thus, to achieve the Pareto improvement between environmental pollution and industrial output growth, it is essential to comprehend the patterns of coal consumption in these industries. Hence, the present research intended to analyze the potential drivers of coal consumption by applying a joint LMDI, DEA, and the production theoretical decomposition approach. Findings indices that, first, industrial output growth was the crucial driver to simulate the industrial coal consumption, while the potential coal intensity and coal technology changes exhibited the reverse effect. Second, the coal inputs and industrial output efficiency, along with the improvements in technological gaps, were found to be the imperative factors in decelerating coal consumption. Third, the energy industrial group was discovered to have more potentials of coal conversation as compared to the non-energy industrial group. Moreover, results also indicated that coal pure technical efficiency is accelerating coal growth, which revealed that coal can be saved by enhancing coal allocative efficiency. These findings laid the empirical ground to design a feasible coal conservation policy for achieving the imperative goals of environmental protection without compromising industrial output growth.
Keywords: Carbon emission; China; Coal consumption; LMDI model; Production-theoretical decompositions; Technological gap.
© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.